Impact of global warming on ENSO phase change

We compare the physical mechanisms involved in the generation and decay of ENSO events in a control (present day conditions) and Scenario (Is92a, IPCC 1996) simulations performed with the coupled ocean-atmosphere GCM ECHAM4-OPYC3. A clustering technique which objectively discriminates common features in the evolution of the Tropical Pacific Heat Content anomalies leading to the peak of ENSO events allows us to group into a few classes the ENSO events occurring in 240 years of data in the control and scenario runs. In both simulations, the composites of the groups show differences in the generation and development of ENSO. We present the changes in the statistics of the groups and explore the possible mechanisms involved

Spatial and temporal analysis of the seasonal and interannual variability in the tropical Pacific simulated with a coupled GCM

In the first part of this work, the dominant time scales that explain the tropical variability of the first SINTEX simulation (ECHAM4(T30)-ORCA) are identified through a spectral analysis. Higher order spectral analysis is used to examine the interactions among these time scales. The time series analyzed are an average of sea surface temperature over the Niño3 region. The time scales obtained are compared with those identified in another coupled GCM simulation (ECHAM4(T42)-OPYC3). The higher importance of the biannual time scale in this last is explained partly by the strength of the coupling between the annual and the biannual time scales. There is no such strong coupling in the SINTEX simulation. Important differences among the generation of the simulated warm (or cold) event suggest the need of a systematic classification to isolate their relevant features. Therefore in the second part of this work, we address this problem. A space-time cluster analysis is performed on a data set built by collecting the values of the heat content anomalies in the tropical Pacific region, in the fifteen months previous to a peak in the Niño3 Index that has been identified as a ‘warm’ (or ‘cold’) event. In the case of the warm events, three types of generation schemes are found. In two of them, there are anomalies of heat content in the west, north and south of the equator, more than nine months before the events start. In the third case, the anomalies appear and grow in the central equatorial Pacific. Only two types are needed to classify the generation of cold events. Negative sea level height anomalies appear six months before the Niño3 Index reaches the (local) minimum. They are located north of the equator in one of the groups, and south of it in the other. Some of these characteristic traits also appear in observations of warm and cold events

Scale interactions in the tropical Atlanticvariability simulated with a coupled GCM

Warm and cold events in the Gulf of Guinea are an important feature in the interannual variability of the tropical Atlantic Ocean, and partly a manifestation of the equatorial Atlantic system's intrinsic variability. Due to the relatively reduced zonal extension of this ocean, the latter variability is comparatively weak and thus strongly modified by other factors at play, either local or remote, like the seasonal cycle or ENSO. We present here an analysis of the tropical Atlantic variability in a 100-year-long chunk of the output of a coupled GCM. Through it, we obtain a better understanding of this variability and of its interactions with the seasonal cycle and with the ENSO signal. Following hints in the observations, we separate warm or cold events of the simulation in a few types, according to their similarities and differences. This classification is carried out as a spatio-temporal cluster analysis of the values, from nine months before up to the peak of the event, of the heat content anomalies. This is an optimal variable to monitor the generation of the events. One of the warm event classes can be explained by ENSO interactions. One of the cold event types can be explained by this influence as well, while the seasonal interactions might explain the characteristics of another of them

Seasonality of coastal upwelling trends in the Mauritania-Senegalese region under RCP8.5 climate change scenario

The Mauritania-Senegalese upwelling region (MSUR), the southernmost region of the Canary current upwelling system, is well-known for its coastal productivity and the key role it plays in enriching the oligotrophic open ocean through the offshore transport of the upwelled coastal waters. The great ecological and socio-economic importance makes it necessary to evaluate the impact of climate change on this region. Hence, our main objective is to examine the climate change signal over the MSUR with a high resolution regional climate system model (RCSM) forced by the Earth system model MPI-ESM-LR under RCP8.5 scenario. This RCSM has a regional atmosphere model (REMO) coupled to a global ocean model (MPIOM) with high-resolution in the MSUR, which allows us to evaluate the wind pattern, the ocean stratification, as well as the upwelling source water depth, while maintaining an ocean global domain. Under RCP8.5 scenario, our results show that the upwelling favourable winds of the northern MSUR are year-round intensified, while the southern MSUR presents a strengthening in winter and a weakening in March–April. Along with changes in the wind pattern, we found increased ocean stratification in the spring months. In those months southern MSUR presents a shallowing of the upwelling source water depth associated to changes in both mechanisms. However, in winter the whole MSUR shows a deepening of the upwelling source water depth due to the intensification of the upwelling favourable winds, with the increased ocean stratification playing a secondary role. Our results demonstrate the need to evaluate the future evolution of coastal upwelling systems taking into account their latitudinal and seasonal variability and the joint contribution of both mechanisms.publishedVersio

Spatial and temporal analysis of the seasonal and interannual variability in the tropical Pacific simulated with a coupled GCM

In the first part of this work, the dominant time scales that explain the tropical variability of the first SINTEX simulation (ECHAM4(T30)-ORCA) are identified through a spectral analysis. Higher order spectral analysis is used to examine the interactions among these time scales. The time series analyzed are an average of sea surface temperature over the Niño3 region. The time scales obtained are compared with those identified in another coupled GCM simulation (ECHAM4(T42)-OPYC3). The higher importance of the biannual time scale in this last is explained partly by the strength of the coupling between the annual and the biannual time scales. There is no such strong coupling in the SINTEX simulation. Important differences among the generation of the simulated warm (or cold) event suggest the need of a systematic classification to isolate their relevant features. Therefore in the second part of this work, we address this problem. A space-time cluster analysis is performed on a data set built by collecting the values of the heat content anomalies in the tropical Pacific region, in the fifteen months previous to a peak in the Niño3 Index that has been identified as a ‘warm’ (or ‘cold’) event. In the case of the warm events, three types of generation schemes are found. In two of them, there are anomalies of heat content in the west, north and south of the equator, more than nine months before the events start. In the third case, the anomalies appear and grow in the central equatorial Pacific. Only two types are needed to classify the generation of cold events. Negative sea level height anomalies appear six months before the Niño3 Index reaches the (local) minimum. They are located north of the equator in one of the groups, and south of it in the other. Some of these characteristic traits also appear in observations of warm and cold events

Sensitivity of simulated regional Arctic climate to the choice of coupled model domain

The climate over the Arctic has undergone changes in recent decades. In order to evaluate the coupled response of the Arctic system to external and internal forcing, our study focuses on the estimation of regional climate variability and its dependence on large-scale atmospheric and regional ocean circulations. A global ocean–sea ice model with regionally high horizontal resolution is coupled to an atmospheric regional model and global terrestrial hydrology model. This way of coupling divides the global ocean model setup into two different domains: one coupled, where the ocean and the atmosphere are interacting, and one uncoupled, where the ocean model is driven by prescribed atmospheric forcing and runs in a so-called stand-alone mode. Therefore, selecting a specific area for the regional atmosphere implies that the ocean–atmosphere system can develop ‘freely’ in that area, whereas for the rest of the global ocean, the circulation is driven by prescribed atmospheric forcing without any feedbacks. Five different coupled setups are chosen for ensemble simulations. The choice of the coupled domains was done to estimate the influences of the Subtropical Atlantic, Eurasian and North Pacific regions on northern North Atlantic and Arctic climate. Our simulations show that the regional coupled ocean–atmosphere model is sensitive to the choice of the modelled area. The different model configurations reproduce differently both the mean climate and its variability. Only two out of five model setups were able to reproduce the Arctic climate as observed under recent climate conditions (ERA-40 Reanalysis). Evidence is found that the main source of uncertainty for Arctic climate variability and its predictability is the North Pacific. The prescription of North Pacific conditions in the regional model leads to significant correlation with observations, even if the whole North Atlantic is within the coupled model domain. However, the inclusion of the North Pacific area into the coupled system drastically changes the Arctic climate variability to a point where the Arctic Oscillation becomes an ‘internal mode’ of variability and correlations of year-to-year variability with observational data vanish. In line with previous studies, our simulations provide evidence that Arctic sea ice export is mainly due to ‘internal variability’ within the Arctic region. We conclude that the choice of model domains should be based on physical knowledge of the atmospheric and oceanic processes and not on ‘geographic’ reasons. This is particularly the case for areas like the Arctic, which has very complex feedbacks between components of the regional climate system

The South Atlantic Anticyclone as a key player for the representation of the tropical Atlantic climate in coupled climate models

The key role of the South Atlantic Anticyclone (SAA) on the seasonal cycle of the tropical Atlantic is investigated with a regionally coupled atmosphere–ocean model for two different coupled domains. Both domains include the equatorial Atlantic and a large portion of the northern tropical Atlantic, but one extends southward, and the other northwestward. The SAA is simulated as internal model variability in the former, and is prescribed as external forcing in the latter. In the first case, the model shows significant warm biases in sea surface temperature (SST) in the Angola-Benguela front zone. If the SAA is externally prescribed, these biases are substantially reduced. The biases are both of oceanic and atmospheric origin, and are influenced by ocean–atmosphere interactions in coupled runs. The strong SST austral summer biases are associated with a weaker SAA, which weakens the winds over the southeastern tropical Atlantic, deepens the thermocline and prevents the local coastal upwelling of colder water. The biases in the basins interior in this season could be related to the advection and eddy transport of the coastal warm anomalies. In winter, the deeper thermocline and atmospheric fluxes are probably the main biases sources. Biases in incoming solar radiation and thus cloudiness seem to be a secondary effect only observed in austral winter. We conclude that the external prescription of the SAA south of 20°S improves the simulation of the seasonal cycle over the tropical Atlantic, revealing the fundamental role of this anticyclone in shaping the climate over this region

Dynamical downscaling of historical climate over CORDEX Central America domain with a regionally coupled atmosphere–ocean model

The climate in Mexico and Central America is influenced by the Pacific and the Atlantic oceanic basins and atmospheric conditions over continental North and South America. These factors and important ocean–atmosphere coupled processes make the region’s climate a great challenge for global and regional climate modeling. We explore the benefits that coupled regional climate models may introduce in the representation of the regional climate with a set of coupled and uncoupled simulations forced by reanalysis and global model data. Uncoupled simulations tend to stay close to the large-scale patterns of the driving fields, particularly over the ocean, while over land they are modified by the regional atmospheric model physics and the improved orography representation. The regional coupled model adds to the reanalysis forcing the air–sea interaction, which is also better resolved than in the global model. Simulated fields are modified over the ocean, improving the representation of the key regional structures such as the Intertropical Convergence Zone and the Caribbean Low Level Jet. Higher resolution leads to improvements over land and in regions of intense air–sea interaction, e.g., off the coast of California. The coupled downscaling improves the representation of the Mid Summer Drought and the meridional rainfall distribution in southernmost Central America. Over the regions of humid climate, the coupling corrects the wet bias of the uncoupled runs and alleviates the dry bias of the driving model, yielding a rainfall seasonal cycle similar to that in the reanalysis-driven experiments.Universidad de Costa Rca/[805-B7-507]/UCR/Costa RicaCRYOPERU/[144-2015]//PerúUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones Geofísicas (CIGEFI

A multi-model ensemble view of winter heat flux dynamics and the dipole mode in the Mediterranean Sea

Changes in surface heat fluxes affect several climate processes controlling the Mediterranean climate. These include the winter formation of deep waters, which is the primary driver of the Mediterranean Sea overturning circulation. Previous studies that characterize the spatial and temporal variability of surface heat flux anomalies over the basin reveal the existence of two statistically dominant patterns of variability: a monopole of uniform sign and an east–west dipole of opposite signs. In this work, we use the 12 regional climate model ensemble from the EU-FP6 ENSEMBLES project to diagnose the large-scale atmospheric processes that control the variability of heat fluxes over the Mediterranean Sea from interannual to decadal timescales (here defined as timescales > 6 year). Our findings suggest that while the monopole structure captures variability in the winter-to-winter domain-average net heat flux, the dipole pattern tracks changes in the Mediterranean climate that are connected to the East Atlantic/Western Russia (EA/WR) atmospheric teleconnection pattern. Furthermore, while the monopole exhibits significant differences in the spatial structure across the multi-model ensemble, the dipole pattern is very robust and more clearly identifiable in the anomaly maps of individual years. A heat budget analysis of the dipole pattern reveals that changes in winds associated with the EA/WR pattern exert dominant control through both a direct effect on the latent heat flux (i.e., wind speed) and an indirect effect through specific humidity (e.g., wind advection). A simple reconstruction of the heat flux variability over the deep-water formation regions of the Gulf of Lion and the Aegean Sea reveals that the combination of the monopole and dipole time series explains over 90 % of the heat flux variance in these regions. Given the important role that surface heat flux anomalies play in deep-water formation and the regional climate, improving our knowledge on the dynamics controlling the leading modes of heat flux variability may enhance our predictability of the climate of the Mediterranean area

Dry season circulation-type classification applied to precipitation and temperature in the Peruvian Andes

We present the first systematic classification of circulation regimes that characterize the Tropical Andes during the dry season (May–August). We apply the hierarchical k-means clustering method to ERA-Interim reanalysis data of daily mean geopotential height at 500- and 200-hPa levels for the period 1981–2015. Specifically, by combining the variability in intensity and location of geopotential anomalies we identify 12 circulation types (CTs). We then establish the relationship between the CTs and surface conditions in the Peruvian Andes (PA) analysing high-resolution gridded datasets of daily mean temperature and rainfall. Our results indicate that intense precipitations and low minimum temperatures are often associated with an Upper Tropospheric Trough (UTT) centred at subtropical latitudes (~30°S) and between 80° and 70°W of longitude. Moreover, drier and warmer conditions across the entire PA region are largely associated with three anticyclonic CTs. Strong negative anomalies in daily maximum (minimum) temperatures can be related to the effect of day (night) cloudiness in the radiative balance, but also to subtropical cold air advections favoured by the UTT. While CTs featuring warmer (colder) conditions have become more (less) frequent in the last decades of the record, there is no systematic link between positive or negative trends in occurrence and the wetter and drier character of the CTs. The annual frequencies of 10 CTs are significantly correlated with El Niño-Southern Oscillation, with warmer and drier (cooler and wetter) CTs generally preceded by an El Niño (La Niña) in the previous wet season